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Record W2930975492 · doi:10.7202/1060948ar

“It Cannot Be Emphasized Enough How Everything Is Interconnected”: Ecological Wisdom, Cross-Cultural Insight, and Pope Francis’ Social Teaching

2019· article· en· W2930975492 on OpenAlexaffvenue
Christopher Hrynkow

Bibliographic record

VenueThe Trumpeter · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Ecology, and Ethics
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsEnvironmental ethicsFlourishingEcological crisisEcologySociologyIndigenousAction (physics)PsychologySocial psychologyPhilosophy

Abstract

fetched live from OpenAlex

When understood as anthropogenic phenomena, contemporary social and ecological crises can be framed as moral issues, arising from human action and neglect of duties to marginalized human and ecological neighbours. In so much as the roots of these problematic outcomes lie in worldview, ecological wisdom can help in fostering spaces for integrated ethical responses to associated challenges like global climate change, social injustice, and ecological delegation. The present article highlights select instances of thinkers who express convergences between social and ecological concern by exploring cross-cultural perspectives on ecological wisdom. Then, with the aid of a green theo-ecoethical viewpoint informed by those perspectives, it maps relevant teachings of Pope Francis that are expressed in two of his most important exercises of his magisterial office: Evangelii Gaudium and Laudato Si’. As brought into view through dialogue with contemporary articulations of ecological wisdom, inclusive of overlapping Indigenous and academic insights, this approach helps discern a noteworthy measure of rhetorical support for socio-ecological flourishing found in the teaching of Pope Francis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.860
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.044
GPT teacher head0.355
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2019
Admission routes2
Has abstractyes

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